Dissertation: Student Acceptance of Mobile Learning

Donaldson, R. L. (2011). Student Acceptance of Mobile Learning. (Doctoral dissertation).

This dissertation was successfully defended April 29, 2011. To help other doctoral students preparing for their defense, I am sharing the  Student Acceptance of Mobile Learning PPT used in my dissertation defense and my prospectus defense PPT. Please be aware that modifications were made to the study after my prospectus defense and there are notes included in the slides. Should you be interested, here is a brief summary document with charts provided to the college and the interview questions.

The study examined:

  • Determinants of student acceptance of mobile learning
  • Student current information seeking and learning on mobile devices
  • Perceptions regarding mobile academic communication
  • Current access to IT, Library, and academic related content

The information gleaned from the results of this study will provide administrators, educators, and librarians with knowledge of determinants of student intention to use and actual use of mobile devices to access academic content in a community college setting.

iXray by Andreas Schaefer

iXray by Andreas Schaefer

The purpose of this mixed method study was to test the determinants of the behavioral intention to use mobile learning by community college students and to discover if there exist either age or gender differences in the acceptance of mobile learning. In addition, I sought to determine how applicable the UTAUT theoretical model and the additional variables, voluntariness of use, perceived playfulness and self-management of learning are in explaining student behavioral intention to use mobile devices for learning.

The results from analyzing the mobile learning survey indicate that performance expectancy, social influence, perceived playfulness of learning, and voluntariness of use were all significant determinants of behavioral intention to use mobile learning. Effort expectancy and self-management were not found to be significant predictor variables. No age or gender differences were found. This research provides useful information in understanding the drivers of acceptance for mobile learning in order to take proactive interventions for students that may be less inclined to adopt mobile learning.

Wang, et al., (2008) Coefficients and Donaldson, (2011) Coefficients

Wang, et al., (2008) Coefficients and Donaldson, (2011) Coefficients

 

Mobile Learning Model

Mobile Learning Model with Beta Coefficients (Donaldson, 2011) *p <0.05; **p <0.01.